Thomson Reuters Labs is seeking scientists to solve problems using state-of-the-art information retrieval, natural language processing, and generative AI to support the organization and its customers through applied research and innovation, clearing obstacles to innovation and incubating AI solutions.
Requirements
- 7+ years of hands-on experience building IR / NLP systems for commercial applications
- A demonstrated impact-focused and velocity-first mindset with the the ability and inclination to architect/develop end-to-end solutions for problems in focused workshop settings
- Experience writing production code and ensuring well-managed software delivery
- Demonstrable experience translating complex problems into successful AI applications
- Professional experience scaling yourself and leading through others, in an applied research setting
Responsibilities
- Lead Applied Scientists are experts in Machine Learning / NLP, responsible for the design and delivery of AI solutions that enhance Thomson Reuters' products.
- They leverage information retrieval techniques, context engineering, model development and evaluation design to build and optimize solutions.
- Their work ensures AI technologies are effectively aligned with business objectives, driving product innovation and value.
- Innovate and drive solution delivery as a technical leader
- Develop in-depth knowledge of customer problems and data
- Maintain scientific and technical expertise in one or more relevant areas as demonstrated through product deliverables, published research, and/or intellectual property.
- Mentor and coach other scientists and engineers on best practices
Other
- Provide input to the business and Labs leadership on long term AI strategy.
- Lead and drive stakeholder engagement with other functions (UX, Product, Tech)
- PhD in a relevant discipline or Master’s plus a comparable level of experience
- Outstanding communication, problem solving, and analysis skills
- Collaborating with Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback
